audio-metrics-cli 0.3.1

Voice Acoustic Analyzer - Professional audio metrics extraction

Audio Metrics CLI

🎙️ Cross-platform audio analysis toolkit for speech metrics extraction

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🚀 Quick Start

Installation

# Install from PyPI (recommended)
pip install audio-metrics-cli

# Or install from source (development)
git clone https://github.com/i-whimsy/audio-metrics-cli.git
cd audio-metrics-cli
pip install -e ".[dev]"

Basic Usage

# Analyze audio file
audio-metrics analyze your_audio.wav --output result.json

# With verbose output
audio-metrics analyze audio.mp3 --verbose --show-progress

# Transcribe only
audio-metrics transcribe audio.m4a -o transcript.txt

# Compare two audio files
audio-metrics compare v1.wav v2.wav

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📦 Features

Core Metrics

• 🎵 Audio Information: Duration, sample rate, file size
• 🗣️ Voice Activity Detection: Speech/silence segmentation
• 📝 Speech-to-Text: Whisper-powered transcription
• 🎼 Prosody Analysis: Pitch, energy, speech rate
• 😊 Emotion Recognition: Emotional state detection (optional)
• 🔤 Filler Word Detection: "um", "uh", "like" detection

Supported Formats

• ✅ WAV
• ✅ MP3
• ✅ M4A
• ✅ FLAC
• ✅ OGG

Cross-Platform

• ✅ Windows
• ✅ macOS
• ✅ Linux

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📖 Documentation

Command Line Interface

analyze - Full Analysis

audio-metrics analyze audio.wav [OPTIONS]

Options:
  -o, --output PATH        Output JSON file path
  -c, --config PATH        Configuration file
  -m, --model TEXT         Whisper model (tiny/base/small/medium/large)
  --no-emotion            Skip emotion analysis
  --show-progress         Show progress bars
  -v, --verbose           Verbose output
  --help                  Show this message

transcribe - Speech to Text

audio-metrics transcribe audio.wav [OPTIONS]

Options:
  -o, --output PATH       Output transcript file
  -m, --model TEXT        Whisper model
  --language TEXT         Language code
  --help                  Show this message

compare - Compare Audio Files

audio-metrics compare audio1.wav audio2.wav [OPTIONS]

Options:
  --format TEXT          Output format (text/json/markdown)
  --help                 Show this message

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📊 Output Example

{
  "audio_info": {
    "duration_seconds": 185.2,
    "sample_rate": 44100,
    "file_size_mb": 2.8
  },
  "vad_analysis": {
    "speech_ratio": 0.81,
    "pause_count": 23,
    "avg_pause_duration": 1.1
  },
  "speech_metrics": {
    "words_total": 820,
    "words_per_minute": 266
  },
  "prosody_metrics": {
    "pitch_mean_hz": 145.3,
    "energy_cv": 0.33
  },
  "filler_metrics": {
    "filler_word_count": 18,
    "fillers_per_100_words": 2.2
  }
}

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🔧 Configuration

Create a config.json file:

{
  "models": {
    "speech_to_text": {
      "provider": "whisper",
      "model": "base",
      "device": "auto"
    },
    "vad": {
      "provider": "silero",
      "threshold": 0.5
    }
  },
  "audio_analysis": {
    "enable_pitch": true,
    "enable_energy": true,
    "enable_pause": true
  },
  "features": {
    "enable_emotion": true,
    "skip_if_too_long": 3600
  }
}

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💻 Development

Setup Development Environment

# Clone repository
git clone https://github.com/i-whimsy/audio-metrics-cli.git
cd audio-metrics-cli

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/

# Format code
black src/
ruff check src/

Project Structure

audio-metrics-cli/
├── src/
│   └── audio_metrics/
│       ├── cli.py              # CLI entry point
│       ├── config.py           # Configuration
│       └── modules/            # Core modules
│           ├── audio_loader.py
│           ├── vad_analyzer.py
│           ├── speech_to_text.py
│           ├── prosody_analyzer.py
│           ├── emotion_analyzer.py
│           ├── filler_detector.py
│           ├── metrics_builder.py
│           └── json_exporter.py
├── tests/
├── examples/
├── pyproject.toml
└── README.md

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🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

• OpenAI Whisper - Speech-to-text
• Silero VAD - Voice activity detection
• Librosa - Audio analysis
• SpeechBrain - Emotion recognition

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📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [e-mail]

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Built with ❤️ by OpenClaw Team